At a Glance
- Tasks: Build cutting-edge data infrastructure for a world-class commodities hedge fund.
- Company: Join a dynamic team backed by a major global conglomerate.
- Benefits: Competitive salary up to £135k, hybrid work, and real impact on projects.
- Other info: Be part of a lean team where your contributions are visible and valued.
- Why this job: Shape the future of trading with no legacy systems holding you back.
- Qualifications: Proficient in Python, PySpark, and familiar with real-time data streaming.
The predicted salary is between 112500 - 137500 £ per year.
You get to build something from nothing, with the backing of one of the largest conglomerates in the world behind you.
This is a fund that has spun out of a major global conglomerate.
They have the capital, the ambition, and the mandate to build a world-class commodities hedge fund right here in the UK.
Everything is greenfield.
No legacy systems, no inherited mess, no technical debt from ten years ago that nobody wants to touch.
You are joining at the start.
That means the architecture decisions you make now are the ones that stick.
You are working directly with high volumes of real-time market data and building the data infrastructure that a serious trading operation will run on.
What makes this different from most data roles is that you are not being put in a box.
There is no ringfenced data team sitting separately from the engineers.
You will work across both disciplines, picking up skills on both sides and becoming a genuinely well-rounded engineer rather than a narrow specialist.
The team is lean, which means your work is visible and your impact is real.
You are comfortable working with Python and Py Spark, and you know your way around DLT and workflow management tools like Prefect or Temporal.
Real-time data streaming systems such as NATS. io or Kafka are familiar territory.
You have built reliable integration services, developed end-to-end data ingestion pipelines, and you take data quality seriously.
Schema and catalogue management and Postgres round out what you are bringing.
This is a hybrid role based in the UK.
Ready to build something that actually matters from day one?
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Data Engineer - Commodities Hedge Fund - Up to £135k employer: Saragossa
Saragossa is an exceptional employer located in the vibrant city of London, offering a dynamic work culture that fosters innovation and collaboration. As a member of our team, you'll enjoy meaningful growth opportunities while working on cutting-edge ML-driven projects that directly impact our research platform. With a focus on real ownership and a clean-slate environment, we empower our employees to turn ideas into actionable strategies, making your contributions truly valuable.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer - Commodities Hedge Fund - Up to £135k
✨Get Involved in Data Science Meetups
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Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Engineer - Commodities Hedge Fund - Up to £135k at Saragossa.
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Saragossa.
✨Apply Directly through Our Website
When you find a suitable opening like Data Engineer - Commodities Hedge Fund - Up to £135k at Saragossa, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Data Engineer - Commodities Hedge Fund - Up to £135k
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Saragossa, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Saragossa. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Saragossa
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Saragossa!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
